Studying 'up' in migrant entrepreneurship: Privileged migrant entrepreneurs in Wroclaw, Poland
Bibliographic record
Abstract
While most studies of migrant entrepreneurship focus on disadvantaged migrants from the ‘global South’, this study does the opposite and explores the entrepreneurial activities of migrants from economically advanced countries. In doing so, the study fills a gap in the literature by studying ‘up’ (Nader 1972; Gusterson 1997; Aguiar 2012) and, subsequently, creates a counterpoint against which it critically examines the current ‘downward’ facing theoretical approaches within the field of migrant entrepreneurship. Moreover, this study carries wider implications in terms of global inequality by closely scrutinising entrepreneurs from some of the world’s wealthiest nations and positioning these findings against those from those from some of the poorest. Data is drawn primarily from 65 qualitative interviews with 41 migrant entrepreneurs from core-states (the UK, the USA, Italy, France, Germany, Ireland, Finland, Portugal, Canada, Australia, and Israel) and 24 from periphery-states (Ukraine, Belarus, India, Nigeria, and South Africa) in the shared ‘middle-ground’, semi-periphery environment of Wroclaw, Poland. Guided by the principles of Grounded Theory (Glaser & Strauss 1967), the study reveals previously invisible assumptions and structures, subsequently offering several empirical contributions to the field of migration and migrant entrepreneurship. In order to account for these findings, a theoretical contribution is also offered by proposing the concept of ‘Global-embeddedness’. In doing so, the study reinforces calls for scholars to ‘jettison’ the nation-state as the largest unit of analysis (Schiller & Faist 2013: 5) and extends such a multilateral, global approach into the field of migrant entrepreneurship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".